1. Field of the Invention
The present invention relates to intelligent safety monitoring technology and more particularly, to a neural network-controlled automatic tracking and recognizing system comprised of a fixed field of view collection module, a full functions variable field of view collection module, a video image recognition algorithm module, a neural network control module, a suspect object track-tracking module, a database comparison and alarm judgment module, a monitored characteristic recording and rule setting module, a light monitoring and control module, a backlight module, an alarm output/display/storage module, and security monitoring sensors.
2. Description of the Related Art
Following development of human civilization, people have strong demand for security. The developing trend of intelligent security technology has been changed from investigation after event to “preserving before event, prohibiting in the event and rapid dissolving after the event”.
Many safety monitoring and control systems are known. However, conventional safety monitoring and control systems are still not satisfactory in function and have the following common drawbacks: 1. Fixed monitoring images, not able to catch characteristics of suspect object clearly, having dead corner in catching images, making after event investigation difficult; 2. No capability in preserving before event, no intelligent algorithm, no self-learning ability, no ability in detecting behavior of moving object against rule (such as detection on cross border, direction, cluster, etc.), no ability to identify identity of suspect object by means of biological recognition technology to achieve a preserving measures; 3. Not able to track the motion track and detail characteristics of suspect object; 4. Requiring a big amount of cameras, storage devices and main power to achieve monitoring operation.
There are advanced systems capable of recognizing behaviors of violation of moving object against rule, stealing behavior and properties left. However, these systems simply use sensing cameras to match with a computer for recognition and alarm, they cannot eliminate the problems of dead corner in catching images, being unable to track the motion track of suspect object and non-clearness detail characteristics of suspect object. More particularly, the small suspect object image scale causes recognition of identity of suspect object difficult.